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Record W4212872437 · doi:10.1186/s12896-022-00737-7

An efficient and specific CRISPR-Cas9 genome editing system targeting soybean phytoene desaturase genes

2022· article· en· W4212872437 on OpenAlexafffund
Qing Lu, Lining Tian

Bibliographic record

VenueBMC Biotechnology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsBiologyPhytoene desaturaseCRISPRGenome editingGeneCas9GeneticsGenomeComputational biologyGene silencing

Abstract

fetched live from OpenAlex

BACKGROUND: Genome editing by CRISPR/Cas9 has become a popular approach to induce targeted mutations for crop trait improvement. Soybean (Glycine max L. Merr.) is an economically important crop worldwide. Although gene editing has been demonstrated in soybean, its utilization in stably transformed plants through whole plant regeneration is still not widespread, largely due to difficulties with transformation or low mutation efficiencies. RESULTS: We sought to establish a simple, efficient, and specific CRISPR/Cas9 system to induce heritable mutations in soybean through stable transformation. We targeted phytoene desaturase (PDS) genes due to the distinctive dwarf and albino phenotypes of the loss of function mutant. To evaluate gene editing efficiency and specificity, three constructs targeting each of the two homologous soybean PDS genes specifically, as well as two constructs targeting both simultaneously with one guide RNA were created. Instead of using cotyledonary nodes from germinated seedlings, we used 'half-seed' explants derived from imbibed seeds for Agrobacterium-mediated transformation of cultivar Williams 82. Transformed plants for all five constructs were recovered. Dwarf and albino phenotypes were observed in transgenic plants harboring the constructs targeting both PDS genes. Gene editing at the desired loci was detected in the majority of T0 transgenic plants, with 75-100% mutation efficiencies. Indel frequencies varied widely among plants (3-100%), with those exhibiting visible mutant phenotypes showing higher frequencies (27-100%). Deletion was the predominant mutation type, although 1-nucleotide insertion was also observed. Constructs designed to target only one PDS gene did not induce mutation in the other homologous counterpart; and no mutation at several potential off-target loci was detected, indicating high editing specificity. Modifications in both PDS genes were transmitted to T1 progenies, including plants that were negative for transgene detection. Strong mutant phenotypes were also observed in T1 plants. CONCLUSIONS: Using simple constructs containing one guide RNA, we demonstrated efficient and specific CRISPR/Cas9-mediated mutagenesis in stably transformed soybean plants, and showed that the mutations could be inherited in progenies, even in plants that lost transgenes through segregation. The established system can be employed to edit other genes for soybean trait improvement.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.244
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations41
Published2022
Admission routes2
Has abstractyes

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